ArticleJMIR medical education2025
Perceptions and Earliest Experiences of Medical Students and Faculty With ChatGPT in Medical Education: Qualitative Study.
Article in JMIR medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Application of AI-Generated Content in Medical Education: Systematic Review of the Impact on Critical Thinking Abilities of Medical Students.JMIR medical education · 2026Pooled it
- Artificial intelligence in reproductive medicine and education: current evidence, challenges, and future directions.Journal of assisted reproduction and genetics · 2026Review
- Saudi Medical Students' Perceptions and Attitudes of Integrating Generative Artificial Intelligence Integration in Medical Education: A Cross-Sectional Study.Health science reports · 2026Article
- From hype to reality: the feasibility, dilemmas, and solutions of Gen AI in medical education from students' perspectives.BMC medical education · 2026Article
- Principles for medical students' responsible use of generative AI: a student-partnered Delphi study.BMC medical ethics · 2026Article
- Diagnostic accuracy and citation integrity of four large language models on otolaryngology vignettes.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- Acceptance and use of GenAI among medical and health sciences students in Saudi Arabia: an extended TAM study.BMC medical education · 2026Article
- Authoritative Textbook-Augmented Large Language Models for High-Altitude Public Health Medical Education in the Xizang Autonomous Region: Cross-Sectional Comparative Evaluation Study.Journal of medical Internet research · 2026Article
- Faculty Perspectives on AI Integration in Anatomy Education in the United Arab Emirates: Cross-Sectional Survey.JMIR medical education · 2026Article
- Technostress in the Era of Generative Artificial Intelligence: Mental Health Implications in Medical Education.Psychiatry investigation · 2026Article
- [Artificial intelligence and disinformation in health: The need for re-education from primary care].Atencion primaria · 2026Review
- Trust Analysis Canvas for Teaching in the Field of Digital Public Health and Medicine: Tutorial.JMIR medical education · 2026Article
- A scoping review of the use of generative artificial intelligence tools in health profession education.BMC medical education · 2026Article
- Bridging the mentorship divide: how large language models could reshape medical workforce equity.NPJ digital medicine · 2026Article
- ChatGPT in medical education: a cross-sectional analysis of usage, attitudes, perceptions, and practices among Saudi medical students.Frontiers in artificial intelligence · 2026Article
- Preparing tomorrow's physicians for AI-driven healthcare: insights from a study on medical students', interns', and residents' knowledge, attitudes, and educational needs.Frontiers in medicine · 2026Article
- Use and Perceptions of Generative Artificial Intelligence Tools Among First-Year Medical Students: A Cross-Sectional Survey.Advances in medical education and practice · 2026Article
- Internship Learning Experiences, Challenges, and Resource Preferences Among Junior Doctors in Two Malaysian Tertiary Hospitals: A Pilot Study on the Preliminary Validation of a Multifaceted Questionnaire.Advances in medical education and practice · 2026Article
- Causal Inference, Statistical Assumptions, and Natural-Language-Processing Artefacts in Evaluating Medical Students' Use of Generative Artificial Intelligence [Letter].Advances in medical education and practice · 2026Article
- Mapping applications and evaluations of LLM-enabled AI chatbots for health purposes: a scoping review.Frontiers in public health · 2026Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWith the rapid development of artificial intelligence technologies, there is a growing interest in the potential use of artificial intelligence-based tools like ChatGPT in medical education. However, there is limited research on the initial perceptions and experiences of faculty and students with ChatGPT, particularly in Saudi Arabia.
objectiveThis study aimed to explore the earliest knowledge, perceived benefits, concerns, and limitations of using ChatGPT in medical education among faculty and students at a leading Saudi Arabian university.
methodsA qualitative exploratory study was conducted in April 2023, involving focused meetings with medical faculty and students with varying levels of ChatGPT experience. A thematic analysis was used to identify key themes and subthemes emerging from the discussions.
resultsParticipants demonstrated good knowledge of ChatGPT and its functions. The main themes were perceptions of ChatGPT use, potential benefits, and concerns about ChatGPT in research and medical education. The perceived benefits included collecting and summarizing information and saving time and effort. However, concerns and limitations centered around the potential lack of critical thinking in the information provided, the ambiguity of references, limitations of access, trust in the output of ChatGPT, and ethical concerns.
conclusionsThis study provides valuable insights into the perceptions and experiences of medical faculty and students regarding the use of newly introduced large language models like ChatGPT in medical education. While the benefits of ChatGPT were recognized, participants also expressed concerns and limitations requiring further studies for effective integration into medical education, exploring the impact of ChatGPT on learning outcomes, student and faculty satisfaction, and the development of critical thinking skills.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.